Traditional reactive power optimization mainly considers the constraints of active management elements and ignores the randomness and volatility of distributed energy sources, which cannot meet the actual demand. Therefore, this paper establishes a reactive power optimization model for active distribution networks, which is solved by a second-order cone relaxation method and interval optimization theory. On the one hand, the second-order cone relaxation technique transforms the non-convex optimal dynamic problem into a convex optimization model to improve the solving efficiency. On the other hand, the interval optimization strategy can solve the source−load uncertainty problem in the distribution network and obtain the interval solution of the optimization problem. Specially, we use confidence interval estimation to shorten the interval range, thereby improving the accuracy of the interval solution. The model takes the minimum economy as the objective function and considers a variety o... [more]

The emergence of distributed generation such as solar systems has introduced new challenges in distribution networks that are becoming more apparent with increasing penetration levels. The time mismatch between peak load and peak generation can make voltage levels in distribution networks swing towards extreme limits during a day. Distribution network service providers are struggling to cater for new distributed generation installations while ensuring that the quality of steady state supply voltage meets stipulated requirements. The segregation between medium and low voltage networks in control strategies may result in unnecessary or worse, opposing control actions leading to voltage issues and control on one side of the distribution network influencing the other. By developing an efficient volt/var control method, the steady state voltage level and voltage unbalance in a comprehensive distribution network can be controlled simultaneously. This paper analyses voltage issues and volt/va... [more]

The operation of a power system with 100% converter-interfaced generation poses several questions and challenges regarding various aspects of the design and the control of the system. Existing literature on the integration of renewable energy sources in isolated systems mainly focuses on energy aspects or steady-state issues, and only a few studies examine the dynamic issues of autonomous networks operated with fully non-synchronous generation. A lack of research can be found in particular in the determination of the required amount of grid-forming power, the selection of the number and rated power of the units which should implement the grid-forming controls, and the relative locations of the grid-forming converters. The paper aims to address those research gaps starting from a theoretical point of view and then by examining the actual electrical network of an existing island as a case study. The results obtained from the investigations indicate specific observations and design opport... [more]

The low-carbon transformation of the power industry is of great significance to realize the carbon peak in advance. However, almost a third of China’s CO2 emissions came from the power sector in 2019. This paper aimed to identify the key drivers of CO2 emissions in China’s power industry with the consideration of spatial autocorrelation. The spatial Durbin model and relative importance analysis were combined based on Chinese provincial data from 2003 to 2019. This combination demonstrated that GDP, the power supply structure and energy intensity are the key drivers of CO2 emissions in China’s power industry. The self-supply ratio of electricity and the spatial spillover effect have a slight effect on increasing CO2 emissions. The energy demand structure and CO2 emission intensity of thermal power have a positive effect, although it is the lowest. Second, the positive impact of GDP on CO2 emissions is decreasing, but that of the power supply structure and energy intensity is increasing.... [more]

Crossplot is an important tool for data visualization analysis in well logging processing and interpretation. Generally, the color of the points in the crossplot is calibrated by the data to improve the plane crossplot from two dimensions (2D) to three dimensions (3D). However, this method is limited to the logging data. In many cases, it is necessary to use crossplots for comprehensive evaluation with the well logging, geology, mud logging, and oil testing data, or to deeply analyze the data from multiple wells and multiple layers. The traditional crossplots cannot meet the demands. To expand the traditional crossplot to multiple dimensions, we proposed an augmented-dimensional visualization and analysis method by the crossplot with multi-well and multi-dimensional heterogeneous data, which is developed based on the traditional crossplots. Firstly, we built the match matrix of the augmented-dimensional heterogeneous data from different depths and set up the crossplots of the heterogen... [more]

Data-driven services offer a major shift away from traditional monitoring and control approaches that have been applied exclusively over the transmission and distribution networks. These services assist the electricity value chain stakeholders to enhance their data reach and improve their internal intelligence on electricity-related optimization functions. However, the penetration of data-driven services within the energy sector poses challenges across the regulatory, socioeconomic, and organizational (RSEO) domains that are specific to such business models. The present review examines the existence and importance of various obstacles across these domains regarding innovative energy services, new business models, data exchanges, and other actors’ synergies across the electricity data value chain. This research is centered around the European landscape, with a particular focus on the five demonstration countries (Greece, Spain, Austria, Finland, and Croatia) of the SYNERGY consortium. A... [more]

A recent survey of cybersecurity assessment methods proposed by the scientific community revealed that their practical adoption constitutes a great challenge. Further research that aimed at identifying the reasons for that situation demonstrated that several factors influence the applicability, including the documentation level of detail, the availability of supporting tools, and the continuity of support. This paper presents the European Energy Information Sharing and Analysis Centre (EE-ISAC)—a cybersecurity platform for the energy sector that has been adopted by multiple organisations. The platform facilitates sharing information about cybersecurity incidents, countermeasures, and assessment results. Prospectively, it is envisaged to be integrated with the threat intelligence platform that enables real-time situational awareness. By considering both fault and attack scenarios together, threat awareness can be mapped onto operational contexts to prioritise decisions and responses. Th... [more]

Companies in the energy sector, due to their important role in the economy and the specificity of energy sources, are exposed to many types of risk, ranging from the risk associated with the company’s operations and the global economic and political situation in the world. Energy companies are usually large capital companies whose shares are listed on the stock market. The mentioned risk factors may shape the risk level of these companies. The study aims to examine the relationship between market and accounting risk measures for Polish energy companies listed on the Warsaw Stock Exchange. This paper uses market and accounting betas in the conventional and downside approach. In addition to market measures of total risk, it also examines the variability of ROA for energy companies. The study of the relationship between market risk measures and accounting risk measures was based on Pearson’s correlation coefficient, standard linear regression, and quantile regression. The relationship bet... [more]

This paper presents a stability analysis for droop-based islanded AC microgrids via an autonomous shooting method based on bifurcation theory. Shooting methods have been used for the periodic steady-state analysis of electrical systems with harmonic or unbalanced components with a fixed fundamental frequency; however, these methods cannot be directly used for the analysis of microgrids because, due to the their nature, the microgrids frequency has small variations depending on their operative point. In this way, a new system transformation is introduced in this work to change the droop-controlled microgrid mathematical model from an non-autonomous system into an autonomous system. By removing the explicit time dependency, the steady-state solution can be obtained with a shooting methods and the stability of the system calculated. Three case studies are presented, where unbalances and nonlinearities are included, for stability analysis based on bifurcation analysis; the bifurcations ind... [more]

In this paper, we investigate the enhancement of RF−RF energy harvesting efficiency (erf−rf) in multipath environments in the context of wireless power transfer (WPT). For this, we used a retrodirective transmitting (Tx) antenna array resonating at 2.4 GHz and a receiving (Rx) antenna surrounded by scatterers placed in the Rx near field. The Rx resides in the Tx far field. We showed that in a medium made of a random distribution of scatterers, a time-reversed wave field interacts with the random medium to regenerate not only the propagating waves but also the evanescent waves required to refocus the energy at the receiver location. The system was enclosed inside a 3 m3 cubical reverberating room to create a strong multipath environment. The study was done for homogeneous (free space) and heterogeneous (multipath environment) media. Different WPT scenarios were considered for different applications: 4 × 1, 4 × 2 and 4 × 4 multi input-multi output (MIMO) systems. The simulation results s... [more]

The COVID-19 pandemic has caused a loss of the sense of financial security among employees. The consequence is decreased productivity, affecting employers who also suffer related costs. Actions to support employees’ financial wellness are therefore important and necessary, especially in the case of those working in the strategic sector ensuring national energy security. The main aim of the article is to present, from the theoretical and practical point of view, the essence and role of Employee Financial Wellness Programs (EFWPs) in the creation of an effective incentive system in energy sector companies in Poland during the crisis caused by the COVID-19 pandemic. The following research methods were used: critical analysis of source literature, comparative analysis of existing data and the descriptive method with elements of deductive reasoning. In order to collect primary data, the indirect survey method was used, namely, the CAWI Internet survey technique, which was addressed to the m... [more]

This paper addresses the problem of Distribution Systems Reconfiguration (DSR), which consists of finding the state of switching devices (open or closed) in a given distribution network, aiming to minimize active power loses. DSR is modeled as a mixed-integer non-linear optimization problem, in which the integer variables represent the state of the switches, and the continuous variables represent the power flowing through the branches. Given the multi-modal and non-convex nature of the problem, an improved harmony search (IHS) algorithm is proposed to solve the DSR problem. The main novelty of this approach is the inclusion of a Path Relinking phase which accelerates convergence of the DSR problem. Several tests were carried out in four benchmark distribution systems, evidencing the effectiveness and applicability of the proposed approach.

In this paper, we present problems connected with voltage fluctuations in low-voltage networks caused by small PV sources installed in an LV network. For the purpose of analysis, high-resolution data gathered at the output of real PV sources for 4 months in 2 locations are used. Data are processed to analyze the impact of different network parameters on voltage fluctuations and voltage flicker. The resulting values of flicker and fluctuations are given so the assessment of the impact of PV sources can be made before the connection of new sources to the power grid. Moreover, the methodology of analysis is presented in detail so the impact of similar PV sources on voltage could be analyzed. Finally, general conclusions connected with measurement, analysis, and mitigation are given.

This work proposes a dual-domain maximum power tracking (MPPT) technique for multiple-input RF energy harvesting systems. A differential rectifier array is used to implement 4-channel reconfigurable RF to DC power conversion, and an adjustable 4-bit capacitor array is designed to improve the impedance matching between the antennas and the rectifiers. Using the perturbation and observation (P&O) method, both arrays are adaptively configured in the background with the variations of the input energy and output loading. Experimental results show that the proposed circuit successfully tracks the maximum power points while harvesting RF energy, with the peak conversion efficiency of 49.06% when the input energy is −6 dBm. With the proposed dual-domain MPPT, the high efficiency range of the energy harvesting system is greatly extended to 21 dB (−21−0 dBm).

Reactive power optimization of distribution networks is of great significance to improve power quality and reduce power loss. However, traditional methods for reactive power optimization of distribution networks either consume a lot of calculation time or have limited accuracy. In this paper, a novel data-driven-based approach is proposed to simultaneously improve the accuracy and reduce calculation time for reactive power optimization using ensemble learning. Specifically, k-fold cross-validation is used to train multiple sub-models, which are merged to obtain high-quality optimization results through the proposed ensemble framework. The simulation results show that the proposed approach outperforms popular baselines, such as light gradient boosting machine, convolutional neural network, case-based reasoning, and multi-layer perceptron. Moreover, the calculation time is much lower than the traditional heuristic methods, such as the genetic algorithm.

Connecting photovoltaic micro-installations to a low-voltage network changes the operating conditions of the network. As a result, in certain situations, the permissible operating limits may be periodically exceeded. The risk of exceeding the normal operating conditions of the network depends on multiple factors, including the installed capacity of the photovoltaic sources. In this article, we use a time-series method to determine the annual risks of exceeding the bus voltage limits, the rated current of the lines and transformer, and the acceptable limit of the negative sequence component of bus voltage, as well as the risk of a reverse flow occurring, and the risk of energy losses increasing. We calculate these risks for different levels of penetration of the photovoltaic sources, different divisions of the rated power of the photovoltaic sources between individual phases, and different consumer load profiles. We perform calculations on a CIGRE test network using OpenDSS and statisti... [more]

According to the IPCC, a global carbon budget of 400 GtCO2 is required to limit the temperature rise to 1.5 °C with a 67% likelihood by 2050. The finance industry is increasingly committed to ambitious climate targets. In this article, we describe the detailed methodology and energy model architecture of a MATLAB-based integrated energy assessment model for industry-specific 1.5 °C pathways, with a high technical resolution of target parameters as key performance indicators (KPIs). The additionality of OECM 2.0 is the high technical resolution in terms of the level of detail of industry-specific energy demand and supply parameters that can be modeled—a prerequisite to define industry-specific KPIs. We found that a database of industry-sector-specific energy demands and energy intensities, with a consistent methodology, is required to improve the accuracy of calculations in future research. We supplement the technical documentation with the results for a transport scenario.

In this study, the effect of capitalization premium in forest estate markets on forest management and climate change mitigation economics is investigated. It is shown that proportional goodwill in capitalization induces linear scaling of the financial return, without any contribution to sound management practices. However, there is a financial discontinuity, as harvesting deteriorates goodwill. Such deterioration might be partially avoided by entering the real estate market. Conversely, a capitalization premium set on bare land as a tangible asset would increase timber storage and carbon sequestration. Observations indicate that the proportional goodwill is closer to reality within the Nordic Region, resulting in continuity problems.

Changing asset ownership models in the energy sector is spurring established companies and startups to implement customer-centric smart services. In this sense, startups are pioneers of innovative business models, and unbundle the energy value chain to provide various services to final customers. Although service business models have received large attention in the energy sector, the role of startups in service business model innovation (S-BMI) is not fully understood in the literature. To put this into perspective, the proposed work analyzes the six most practiced energy service categories, specifically, Comfort and Heating, Flexibility and Trading, Energy Efficiency and Management, Solar and Microgrid, Charging and Battery, and Energy Software Solutions are taken into account, accompanying service business model archetypes in the energy sector. Data from two different company databases are combined, and a list of 432 startups dealing with energy services are analyzed. The operating r... [more]

This paper concerns very-short-term (5-Minute) forecasting of photovoltaic power generation. Developing the methods useful for this type of forecast is the main aim of this study. We prepared a comprehensive study based on fragmentary time series, including 4 full days, of 5 min power generation. This problem is particularly important to microgrids’ operation control, i.e., for the proper operation of small energy micro-systems. The forecasting of power generation by renewable energy sources on a very-short-term horizon, including PV systems, is very important, especially in the island mode of microgrids’ operation. Inaccurate forecasts can lead to the improper operation of microgrids or increasing costs/decreasing profits for microgrid operators. This paper presents a short description of the performance of photovoltaic systems, particularly the main environmental parameters, and a very detailed statistical analysis of data collected from four sample time series of power generation in... [more]

THe energy-efficient operation of microgrids—a localized grouping of consuming loads (domestic appliances, EVs, etc.) with distributed energy sources such as solar photovoltaic panels—suggests the deployment of Energy Management Systems (EMSs) that enable the actuation of controllable microgrid loads coupled with Artificial Intelligence (AI) tools. Such tools are capable of optimizing the aggregated performance of the microgrid in an automated manner, based on an extensive network of Advanced Metering Infrastructure (AMI). Modular adaptable/dynamic building envelope (ADBE) solutions have been proven an effective solution—exploiting free façade areas instead of roof areas—for extending the thermal inertia and energy harvesting capacity in existing buildings of different nature (residential, commercial, industrial, etc.). This study presents the PLUG-N-HARVEST holistic workflow towards the delivery of an automatically controllable microgrid integrating active ADBE technologies (e.g., PVs... [more]

Employee performance in remote areas is a source of concern for the Saudi Arabian energy sector, which serves as the primary engine of the country’s economy. This research paper aimed to study the impact of social disconnectedness and career advancement on employees’ performance through employee satisfaction as a mediator. The targeted population was employees worked in remote areas in the energy sector. Data were collected using a web-based questionnaire and distributed electronically using social media. A total of 390 respondents participated in this study, and structural equation modeling (SEM) was employed to analyze the collected data. The study findings revealed that career advancement positively impacts employee performance; however, social disconnectedness negatively impacts employees’ performance. Both career and social factors had an indirect effect on employees’ performance through employee satisfaction. Lastly, results demonstrated a positive impact of employee satisfaction... [more]

The design of Passive Power Filters (PPFs) has been widely acknowledged as an optimization problem. This paper addresses the PPF parameters design problem using the novel Manta Ray Foraging Optimization (MRFO) algorithm. Moreover, an analytical method based on Monte Carlo Simulation (MCS) is proposed to investigate the harmonic performance of such an optimally designed PPF with variations in power networks. The MRFO algorithm has shown a superior solution-finding ability, but a relatively higher computational effort in comparison with other recently proposed algorithms. The harmonic performance of the optimal PPF solution with uncertainties was analyzed using the proposed method. The results imply that the optimally designed PPF can effectively attenuate the high-order harmonics and improved the system performance parameters over different operating conditions to continually comply with the standard limits. The proposed MCS method showed that the optimally designed PPF reduced the volt... [more]

This paper presents the use of real-time digital simulator (RTDS) and hardware-in-the-loop (HIL) methods for the validation of an energy management system designed for real low-voltage (LV) distribution networks with a high penetration of renewable energy sources. The system is used to address voltage violations and current overloading issues and allows the network operator to maintain safe and controllable network operations. The applied control strategy and the system software were verified by means of simulations. In this paper, the next stage of system validation using the HIL method is presented. A testbed was designed and developed to test the operation of prototype controllers of the system in flexible and reproducible conditions before installing them in the network. The presented testing platform not only includes the LV network simulator with the power amplifiers needed for closed-loop setup but also additional elements of a real network to which the system is dedicated, i.e.... [more]

This research aims to examine the direct impact of green innovation strategies and the green dynamic capability on green innovation. The indirect effect is also tested, using green organizational identity as a mediator. A cross-sectional and quantitative research approach was used to collect data from energy firms. The results show that green innovation strategies and green dynamic capabilities positively affect the green innovation. The findings also proved that a green organizational identity acts as a mediator. The research outcomes suggest that the role of green organizational identity needs to be verified by firm managers who want to boost green innovation. In the advance era, society is more conscious about the green environment. Managers need a green innovation strategy to achieve green innovation within their firm. This study will help to manage the environmental issues, environmental degradation reductions, and establishment of green programs and products, which will all benef... [more]